Tahir Shahzad Product Manager & Community Builder
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Tag: Product Launch

How to Know If Your Startup Has a Product Problem or a Marketing Problem

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productvsmarketing

Most founders in crisis do the same thing: they guess.

Retention is low, so they assume the product needs more features. They ship for three months. Nothing moves. So they pivot to marketing, hire an agency, run ads, rewrite the homepage. Still nothing. Now they’re six months behind, the runway is shorter, and the board is asking questions they can’t answer.

The problem was never a lack of effort. It was a lack of diagnosis. Before you open Jira to restructure the backlog or double your performance marketing spend, you have to answer a high-stakes question: Does your startup have a product problem or a marketing problem?

A product problem and a marketing problem can look identical from the outside, low signups, flat growth, high churn. But they have completely different causes, and treating one with the cure for the other doesn’t just fail to help. It actively makes things worse.

Why This Distinction Matters More Than You Think

According to CB Insights‘ updated 2024 analysis of 431 failed startups, 43% failed due to poor product-market fit. Only 14% cited poor marketing as a primary cause. Running out of cash affected 70% of failures.

Here’s what that means in plain terms: most founders who think they have a marketing problem actually have a product problem. And the ones who think they have a product problem are sometimes spending engineering cycles on the wrong diagnosis, when the real issue is that the right people are simply not finding them.

Misreading the signal costs money. It costs time. At early stage, it can cost the company.

The Core Distinction: What Are You Actually Measuring?

Before running any diagnostic, it helps to clarify what each problem actually means.

Product Problem: The product is not creating enough value for the people who use it. They try it, they don’t experience the promised outcome, and they leave. It doesn’t matter how many people you get through the door: they won’t stay, they won’t pay, and they won’t tell others.

Marketing Problem: The product creates real value for the people who use it, but not enough of the right people are finding it. The pipeline is broken, the message is wrong, or you’re targeting the wrong segment entirely.

To accurately isolate where your delivery engine is breaking down, you must separate user acquisition from user retention.

what happens after the first meaningful interaction with your product?

what are you actually measuring
what are you actually measuring

Diagnostic Tests

Test 1: The “Leaky Bucket” Retention Curve Test

Pull your cohort retention data. Look at what percentage of users who signed up in any given month are still active 30, 60, and 90 days later. Then look at the shape of the curve.

  • If the curve drops steeply and never flattens, you have a product problem. Users are leaving before they find value, which means the value either isn’t there, isn’t reachable, or isn’t clear.
  • If the curve flattens at a non-zero baseline, meaning a subset of users stick around indefinitely, you likely have a marketing problem. Your product works for someone. The question is whether you’re reaching enough of those people.
  • if your paid users churn at similar rates to your free users, the product problem is real. If free users churn and paid users stick, you have a people problem: you’re getting the wrong users in the door.

This is one of the clearest product-market fit signals available. When retention stabilizes and improves without aggressive intervention, it means the underlying problem your product solves is persistent and painful enough that users return on their own. A curve that never flattens is telling you the opposite.

Test 2: The Source-of-Truth Test

You need to know why users left. The problem is that most founders never ask at the right moment.

On one product I worked on, we added a single survey form directly on the deactivation screen. Not an email sent three days later. Not a follow-up call. Right there, before the user clicked the final confirm button. The design was intentional: one question, a short list of options, and a Submit button. No long form.

The result was that users actually answered it. When people are at the exit point, they are already decided and they are often willing to say why, as long as you make it easy. A five-option list takes three seconds to complete. A blank text box gets abandoned.

The options we gave were simple and honest:

  • It was too hard to use
  • It was missing a feature I needed
  • I found something else that works better for me
  • It was not what I expected when I signed up
  • It was too expensive for the value I got

Those five options map directly to two buckets.

Product bucket: too hard to use, missing a feature, not enough value for the price. These point to a gap between what the product delivers and what the user needed it to do.

Marketing bucket: found something else, not what I expected. These point to a gap between who the product is for and who is actually being reached.

The marketing bucket answers are about fit between the person and the product at the moment of acquisition: they got there through a wrong message, a wrong channel, or wrong targeting. The product bucket answers are about value delivery after acquisition.

  • If 70% or more of your responses fall into the product bucket: rebuild before you recruit.
  • If 70% or more fall into the marketing bucket: your product works, you are just talking to the wrong people in the wrong way.

Test 3: The Word-of-Mouth Test

This is the test most founders forget to run, and it’s one of the most reliable.

Organic word of mouth, meaning referrals that happen through private channels like WhatsApp messages, Slack groups, or direct peer recommendations, is the clearest signal that a product has crossed a value threshold. According to research on organic growth, product retention directly drives new organic user acquisition. The longer and more consistently someone engages with your product, the more they talk about it.

Instead of relying on opinions, assumptions, or internal discussions, look at the data:

Are users referring others without being incentivized to do so?

You can also measure this directly. In one product, we added a simple survey consisting of a single question and a scale. It gave us a lightweight way to track customer satisfaction and sentiment over time. The feedback from real users proved far more valuable than running internal workshops and debating assumptions in meeting rooms. Customers will often tell you exactly how they feel if you make it easy for them.

If you have zero organic referrals after 6+ months and 500+ signups, that is not a marketing problem. People do not stay quiet about products that genuinely help them. They tell someone. The absence of that behavior points to a product that isn’t creating the kind of value that gets talked about.

If you do have organic referrals, even a small trickle, but your overall growth is flat, that’s a marketing problem. You have proof of value. You need distribution.

Test 4: The Sean Ellis Test

Rahul Vohra at Superhuman popularized this for the mainstream. Sean Ellis originally developed it. The question is simple:

“How would you feel if you could no longer use this product?”

  • very disappointed,
  • somewhat disappointed,
  • not disappointed.

If fewer than 40% say “very disappointed,” you have a product problem: specifically, the product is not yet indispensable enough to the people using it. The insight Vohra added to Ellis’s framework: rather than rebuilding features, narrow the segment. Find the users who would say “very disappointed” and understand everything about them. That is your real market.

If 40% or more say “very disappointed” but growth is still stalled: marketing problem. The product has product-market fit, but it’s not reaching the right people at scale.

The Honest Mistake Most Founders Make

In 2025, building became cheaper and faster than ever. This created a new failure mode: founders iterate on the product in response to signals that are actually marketing signals, and they add marketing spend in response to signals that are actually product signals.

The incentive structure makes this worse. Engineers want to build. Marketers want budgets. Both have a professional interest in presenting the problem as solvable through their particular lens.

This is where an independent perspective, someone with no stake in either the product backlog or the media spend, becomes the highest-leverage thing you can invest in. Not to tell you what to build or what to say. But to read the signals you already have and tell you which problem you actually have.

As Sean Ellis’s growth pyramid framework makes clear: sustainable growth only comes after you have unlocked organic. And organic only comes after the product is genuinely worth talking about. You cannot skip this step with ad spend.

A Quick Decision Framework

Use this as a starting point. It’s not a final answer; it’s a map.

Strong signals of a product problem:

☐ Retention curve drops steeply with no flattening, across all user cohorts
☐ Paid users churn at similar rates to free users
☐ Exit interviews cite confusion, lack of value, or unmet expectations
☐ Zero organic referrals after 6+ months
☐ Users engage once and disappear, regardless of channel or campaign
☐ Sean Ellis score below 40% “very disappointed” among active users

Strong signals of a marketing problem:

☐ Retention curve flattens: some users genuinely stick
☐ Paid users stay; free users churn, which points to the wrong audience at the top of funnel
☐ Exit interviews cite “not the right fit,” “signed up thinking it did X,” or “found something else”
☐ You have organic referrals but can’t replicate them at scale
☐ Your best customers came from a narrow, specific channel, and you haven’t doubled down on it
☐ Sean Ellis score above 40%, but only for a small, specific segment

What To Do Next

Once you have identified the bottleneck, use this product management framework to realign your team’s time, budget, and attention on the problem that is actually limiting growth.

If the Signals Point to a Marketing Problem

Stop building features the market has not asked for. Start narrowing your focus.

Find the smallest viable segment where your retention curve is already healthy and users consistently receive value. Then rebuild your growth strategy around those users.

Focus on:

  • Clarifying the value proposition in plain language
  • Identifying the channels where your best customers already spend time
  • Refining your targeting to reach more people who resemble your retained users
  • Testing messaging based on customer outcomes rather than product features
  • Investing in distribution before investing in additional functionality

The goal is not to attract more traffic. The goal is to attract more of the right traffic.

If the Signals Point to a Product Problem

Growth will not fix a product that users do not want to keep using.

Before building new functionality, focus on understanding where users struggle and why they leave.

Prioritize:

  • User interviews with both active and churned customers
  • Onboarding analysis and drop-off investigation
  • In-app surveys and contextual feedback collection
  • UX simplification and friction reduction
  • Reliability, performance, and technical debt improvements

Many teams respond to weak retention by shipping more features. In reality, the fastest path to growth is often making the existing experience easier, faster, and more reliable.

Run a “Bus Factor” Audit on Your Value Proposition

Product and marketing should be able to describe the primary customer outcome using the same language. A useful exercise is to ask both teams independently:

“What can bring an Aha moment to our customer?”

If the answers differ significantly, users are likely experiencing a gap between what is promised and what is delivered.

Focus on:

  • A single primary customer outcome
  • Consistent messaging across marketing and onboarding
  • A clear path to value during the first user session
  • Success metrics that both teams share

The closer the promise and experience become, the easier growth becomes.

Establish Automated Guardrails for User Feedback

Stop guessing what is broken. Implement continuous user research methodologies. Do not wait for quarterly reviews or anecdotal feedback. Use micro-feedback triggers to capture customer signals.

Examples include:

  • Post-onboarding satisfaction surveys
  • Feedback prompts after key actions
  • Churn and cancellation surveys
  • Customer interviews every month
  • Support ticket trend analysis

A simple one-question survey can often reveal more about customer sentiment than hours of internal debate.

If You Still Cannot Tell

Sometimes the signals are mixed.

Retention may be acceptable but inconsistent. Referrals may exist but not at meaningful scale. Different customer segments may behave in completely different ways.

This is not a failure of observation. It usually means one of three things:

  • Both product and marketing need improvement
  • The product solves a real problem, but only for a narrow audience
  • The wrong customer segment is being targeted

These situations are difficult to diagnose from inside the business because teams naturally become attached to their assumptions.

An experienced external perspective can often identify patterns, blind spots, and opportunities much faster than the team can on its own.

The important thing is to follow evidence rather than opinions. Growth problems become easier to solve when you stop asking who is right and start asking what the data is telling you.

📈 Closing Thoughts

if your product relies on aggressive, non-stop ad spend to survive because your natural retention is zero, you do not have a business—you have an expensive marketing campaign.

The data you need is often easier to access than you think, but only if you are measuring it.

Tools like GA4, Usermaven, Mixpanel, Amplitude, and PostHog can help you track retention, activation, user journeys, referrals, and churn. Combined with customer interviews, support tickets, NPS surveys, and Sean Ellis surveys, they provide enough evidence to determine whether you have a product problem, a marketing problem, or a positioning problem.

Most startups do not suffer from a lack of data. They suffer from a lack of synthesis. The signals are scattered across dashboards and conversations, waiting for someone to connect them into a coherent story.

Read those signals correctly, and you’ll know exactly where to focus your next three months of effort. Misread them, and you’ll spend the next quarter solving the wrong problem, only to wonder why nothing moved.

Also Read:

Invisible Transitions; The Real Work of an AI Product Manager
Why Your Product Team Isn’t Shipping (Hint: It’s Not Capacity)

Tahir Shahzad is a Product Manager, Product Owner, and technology consultant with over a decade of experience helping startups and organizations build products people actually use.
If you’re a founder who’s unsure whether your problem is in the product or the pipeline, book a free discovery call to get a diagnosis before you spend another month building or marketing in the wrong direction.

The Prism of Priorities: Seeing Beyond Stakeholder Noise

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prioritization prism

Sometimes I wish I had a Prism of Priorities in my hands.

Not a metaphor, but a real tool. Something I could hold up to every incoming request, every feature idea, every “quick win,” and instantly see its true color; its real weight, its actual impact.

In my mind, it works like light passing through glass. A single request enters as a bright, confident beam, full of urgency and conviction. Then it refracts into a spectrum, revealing what it is truly made of; user value, business impact, technical cost, timing, and sometimes, pure bias.

The Illusion of Clarity

we do not live in a products centric storyland and in reality it might not be as helpful as it sounds.

Because the honest picture of every request would likely create more chaos than clarity. Imagine showing every stakeholder that their “high priority” request breaks into faint, scattered colors when measured against real user needs. Or discovering that multiple “critical” initiatives are simply competing opinions with no grounding in evidence.

As Ben Horowitz said:

“The hard thing about hard things is that there is no formula for dealing with them.”

Prioritization is one of those hard things. There is no perfect framework that removes ambiguity. Only better ways to navigate it.

Products Are Built on Perspectives

Products are not built in isolation. They are shaped by people, and people come with perspectives, incentives, and biases. Every wishlist carries a story;

  • a sales target to hit,
  • a customer complaint to resolve,
  • a feature a competitor just launched,
  • or simply a belief in what “should” work.

This is where many products quietly drift. According to Marty Cagan, the primary responsibility of a product manager on an empowred product tem is to manage two of the four critical products risks: Value and Viability.

The tension lies in that balance. Value is often assumed. Viability is often negotiated. And both can be distorted by internal bias if left unchecked.

The Role of Corporate Diplomacy

This is where corporate diplomacy becomes an essential skill. Not politics for the sake of survival, but structured communication for clarity. It is about guiding conversations in a way that uncovers what truly matters:

  • What problem are we solving?
  • For whom?
  • Why now?

It is about keeping stakeholders engaged while gradually shifting the conversation from opinions to evidence.

  • You listen carefully.
  • You translate requests into hypotheses.
  • You validate them through data, user behavior, and experiments.

Data does not remove bias entirely, but it anchors decisions in something more stable than intuition alone.

You Don’t Need a Prism

We may never get that perfect Prism of Priorities. But perhaps we do not need one.

Because the real craft of product management is not about revealing a single “true color” of every request. It is about navigating the spectrum; understanding where each input fits, filtering what matters, and continuously aligning the product with the problems it is meant to solve.

Or as Steve Jobs famously said:

“Deciding what not to do is as important as deciding what to do.”

Final Thought

A Prism of Priorities would make things easier, but it would also remove the judgment, context, and nuance that define strong product thinking. The real value lies in how we interpret, challenge, and align; not just what we see.

Sitting in the space where clarity is incomplete requires a different kind of discipline; translating urgency into understanding, and opinions into direction. It comes down to choosing what truly moves the product forward, even when the signal is faint and the noise is loud.

If these ideas resonate, or if you see prioritization differently in your own work, there is always value in exchanging perspectives and learning from real experiences across teams and products.

Three Boys, a Barber, and the Biggest Lie About AI Adoption

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ai adoption feature image

We were in a routine discussion when my boss asked a seemingly straightforward question:

How do we encourage cross-functional teams to adopt AI in their workflows; reduce bottlenecks; experiment faster; and improve productivity?

On the surface, this sounds like a tooling problem. Introduce AI tools, train teams, and expect outcomes. But the question took me somewhere else.

The Story I Shared

In a village, a new barber arrived. He was skilled, efficient, and consistent. Word spread quickly. His shop became busy; customers kept increasing day by day.

In the same village, three struggling boys noticed this. They did a rough calculation; number of customers multiplied by price per haircut. To them, it looked like easy money.

They approached the barber and asked:

“What tools do you use?”

He showed them a comb, scissors, and a machine. That was enough for them.

They pooled money, bought the same tools, and opened their own shop.

For a brief moment, things looked promising. Curious customers walked in. There was attention, even excitement. But the boys didn’t have the skill, the discipline, or the understanding of the craft. Haircuts were poorly done. Experiences were ruined. Within days, the village knew. No one returned.

the illuion of tools
the illuion of tools

The tools were right. The outcome was not.

The Parallel With AI Adoption

This is exactly what is happening with AI today. Teams see others using tools like ChatGPT, Claude or many others and assume:

“This is the formula.” So they invest on the tools:

  • Content teams generate copy
  • Developers use AI for code
  • Product teams use it for documentation

But without clarity and structure, the results are inconsistent or even damaging.

Just like the boys with the barber tools.

The First Batch Illusion

The boys did get customers initially because new things attract curiosity. Every product, feature, or workflow change gets a first batch:

  • Early adopters
  • Curious users
  • Internal champions

This phase often creates a false sense of success.

bell curve
bell curve

Read more about the six stages of product lifecycle

The real signal comes later:

  • Do users return?
  • Does quality improve?
  • Does trust increase?

This is where most teams fail.

Where Teams Actually Fail

From my experience across product and agile environments, failures around AI adoption don’t come from lack of tools. They come from:

  • No Skill Development: Teams use AI outputs without understanding context, accuracy, or limitations.
  • No Workflow Integration: AI is added as a layer, not embedded into decision-making or delivery systems.
  • No Validation Loop: Outputs are not tested with real users or real scenarios.
  • No Ownership: No one is responsible for quality when AI is involved.

The result is not acceleration; it is amplified inconsistency.

What the Barber Got Right

The barber’s success was not because of tools. It was because of:

  • Repeated practice, skill built over time
  • Understanding of customer expectations
  • Consistency in delivery
  • Clear ownership of outcomes

Tools were just enablers.

A Better Way to Introduce AI in Teams

Whether it is a barber shop in a village or a modern AI-powered product, the principle remains the same:

Initial attention comes from curiosity. Sustainable growth comes from capability.

If the goal is to reduce bottlenecks and increase productivity, the approach needs to shift:

1. Start with Problems, Not Tools

Identify where teams are actually stuck:

  • Slow documentation
  • Repetitive tasks
  • Decision delays

Then map AI use cases.

2. Build Skill, Not Just Access

Train teams on:

  • Prompting
  • Validation
  • Context awareness

3. Create Feedback Loops

Every AI-assisted output should be reviewed, tested, and improved.

4. Define Ownership

Someone must own the outcome, even if AI assisted in producing it.

Closing Thought

The gap between tool adoption and actual impact is now visible in real numbers.

  • According to McKinsey’s State of AI 2025 report, AI adoption has broadened significantly, with 88% of organizations reporting that they use AI in at least one business function. Yet only a small fraction report meaningful impact on the bottom line.
  • Through 2025/2026, roughly 80% of AI projects are expected to fail to deliver on their projected value. Gartner, RAND Corporation.
  • The 70% Rule: In successful AI implementations, only 10% of the value comes from the algorithm, 20% from technology/data, and 70% from redesigning how work gets done. Boston Consulting Group (BCG)

What this means in practical terms:

  • You may see a 20–40% speed improvement in isolated tasks using AI
  • But you may also introduce quality drops, rework, and decision noise if systems are weak
  • Over time, this can reduce user trust and retention, which directly impacts growth

Teams that pair AI with structured thinking, validation loops, and accountability can see significant gains in speed, cost efficiency, and experimentation.

Teams that don’t will simply move faster in the wrong direction. The tools are not the differentiator. The system behind them is.

If Your Absence Breaks Delivery, Your System is Fragile

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fragile system

I hated it. I was in a difficult conversation with leadership, explaining why we couldn’t ship. The reason? One key person was absent. As a Technical Product Manager, I was new to the setup and hadn’t built this team myself, but I refuse to abandon ownership just because I’m the new person. I was learning from the dynamics of the team and organizational culture.

I realized our delivery was dependent, not designed. If your software delivery engine stops because someone took a sick day, you aren’t running an Agile team; you’re running a bottleneck.

Fixing the Delivery Engine Piece by Piece

I knew I couldn’t fix everything overnight, so I treated the system like a product and started iterating. I focused on shifting from individual dependency to cross-functional ownership.

  • Created Backups & Shared Context: We stopped letting critical workflows live only in people’s heads.
  • Rotated Responsibilities: I ensured knowledge wasn’t locked with one person by rotating tasks during Scrum sprints.
  • Introduced DevOps & Automation: We implemented CI/CD and uptime monitoring to remove manual deployment risks and “surprises”.
  • Distributed Ownership: I gave the team ownership of upcoming deliveries, empowering them to make strategic decisions rather than just executing tasks.

Within a year, the transformation was clear: the products I led no longer depended on a single point of failure.

Useful Findings for Product Leaders

Through this process of Digital Transformation, I discovered three hard truths about modern product delivery:

The “Bus Factor”:

The bus factor is a risk management metric representing the minimum number of team members who, if suddenly unavailable (e.g., hit by a bus), would cause a project to fail due to lack of critical knowledge. A low bus factor (e.g., 1) indicates high risk, while a higher number indicates a resilient team with shared knowledge.

Agile is About Resilience

Agile is often misunderstood as a set of ceremonies or frameworks like Scrum or Kanban.
In reality, Agile is a resilience system. It is the ability of a team to adapt when priorities shift, people change, or uncertainty increases. A truly Agile team does not depend on perfect plans; it is designed to absorb change and continue delivering value.

Documentation is Delivery

When knowledge lives only in people’s heads, it creates hidden dependencies. This leads to delays, confusion, and risk when key individuals are unavailable. This is a form of technical debt that is harder to detect than bad code. Documentation is not overhead.
It is what makes delivery repeatable and reliable.

The “Resilient Delivery” Framework

To reduce these issues in your own organization, I suggest moving away from “hero culture” and toward a system-based framework:

hero culture
hero culture

Pillar 1: Knowledge Liquidity: Use tools like Kanban to visualize not just tasks, but who knows how to do them. If only one name appears on a certain type of ticket, you have a knowledge silo.

Pillar 2: Automated Guardrails: Shift from manual processes to AI-driven automation and CI/CD. Let the machine handle the “how” so the humans can focus on the “why”.

Pillar 3: Strategic Redundancy: Startups don’t have abundance of resources. That requires adaptability essential. Cross-train your team, share context, and enable people to step into adjacent roles when needed.

Closing Thoughts

Look at your setup today: where does everything slow down when one person steps away?. If you are an aspiring Product Manager in or a founder navigating Digital Transformation, don’t wait for a crisis to fix your system. Build for resilience, not just for speed.

By prioritizing shared context and automated guardrails, you ensure that your “product” continues to deliver value even when life happens.

How are you currently handling single points of failure in your delivery process?

Discussion of the Week: Are dashboards becoming outdated now that AI can explain your product data for you?

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dashboards blog featured

For years, product teams relied on dashboards, filters, and exports just to answer basic questions like:

  • What changed in user behavior this week?
  • Which feature actually drove retention?
  • Where are users dropping off?

But the workflow has always been heavy:
Dashboards → Export data → Sheets → Integration tools & Custom Formulas → Back to decisions.

Slow, fragmented, and heavily dependent on human effort to connect the dots.

traditional agentic ai analytics
traditional agentic ai analytics

Even with advanced analytics tools, the reality hasn’t changed much. Teams still spend more time finding insights than actually acting on them.

Now a different model is emerging.

With Agentic AI in product analytics, tools like Usermaven can directly interpret your product data and give contextual summaries without needing extra steps or integrations. Instead of navigating dashboards, you can simply ask and get insights in natural language.

Instead of building workflows around data, insights are becoming part of the workflow itself.

This shifts the conversation from:
“Where do I find the data?”
to
“What is the data trying to tell me?”

This changes the role of analytics from reporting → to reasoning.

A few questions worth discussing:

  • What tools do you use to understand user behavior?
  • Do you export data to LLMs or other tools for analysis?
  • Do you trust AI-generated insights for product decisions?
  • If your analytics tool gives you simple summaries automatically, would you still need other tools?

Previous Edition: Is Cross-Channel Tracking Dead or Just Evolving?

Invisible Transitions; The Real Work of an AI Product Manager

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A Practical Checklist for Managing Product Transitions

There are moments in every product lifecycle when something underneath needs to change.

Sometimes it is small; upgrading a CRM API from V2 to V3 without touching endpoints or user experience.
Sometimes it is messy; a core library gets deprecated, and suddenly your pipelines, integrations, and assumptions need to be rebuilt.
Sometimes it is big; rebranding, domain changes, or platform migrations that can impact trust and discoverability.

Most users should never notice any of this. That is the job.

In today’s AI-driven ecosystem, where models, tools, and libraries evolve almost daily, these transitions are no longer occasional. They are continuous. AI Product Managers are not just building features; they are constantly managing change under the surface.

I have been through all of these transitions, and one principle stays consistent:

If users notice the transition, something was not handled well; unless you intentionally made it visible as an upgrade.

A Practical Checklist for Managing Product Transitions

With AI systems:

  • Dependencies change faster
  • Models become obsolete quickly
  • Vendor lock-in risks increase
  • Experimentation becomes continuous

This means transition management is no longer a side task. It is a core competency.

1. Transition Classification

Start by understanding what kind of change you are dealing with:

  • Silent Upgrade; API versioning, infra improvements
  • Structural Change; library replacement, pipeline redesign
  • Experience Impacting; UI changes, workflows
  • Market-Level Change; rebranding, domain shift

Each category demands a different level of visibility and risk control.

2. Impact Mapping

Before touching anything, map the blast radius:

  • Systems and dependencies affected
  • Data flow and integrity risks
  • User journeys that might break
  • External integrations and partners

This is where most hidden risks surface.

3. Risk Analysis

Break risks into clear buckets:

  • Technical Risk; failures, downtime, performance drops
  • Data Risk; loss, inconsistency, migration errors
  • User Risk; confusion, trust erosion
  • Business Risk; revenue disruption, SEO loss (in case of domain change)

For each risk, define:

  • Likelihood
  • Impact
  • Mitigation strategy

No transition should move forward without this clarity.

4. Stakeholder Buy-In

Transitions fail more due to misalignment than technology.

Internal stakeholders:

  • Engineering; feasibility and timelines
  • Design; experience consistency
  • Marketing; messaging if visible
  • Support; handling edge cases

External stakeholders:

  • Clients and enterprise users
  • Integration partners
  • Third-party vendors

Communicate early. Align expectations. Remove surprises.

5. Execution Strategy

Choose the right rollout model:

  • Phased rollout
  • Feature flags
  • Parallel systems (old + new)
  • Backward compatibility layers

Always have a rollback plan. If you cannot roll back, you are taking unnecessary risk.

6. Observability and Monitoring

Transitions do not end at deployment.

Track:

  • System performance
  • Error rates
  • User behavior changes
  • Drop-offs in key funnels

Set clear success metrics before release.

7. Communication Strategy

Decide what to hide and what to highlight:

  • Keep infrastructure changes invisible
  • Announce improvements that add user value
  • Frame transitions as benefits, not disruptions

Silence is a strategy; so is storytelling.

Final Thoughts

Every product evolves; APIs change, dependencies break, platforms shift. In the AI era, this pace is no longer manageable with reactive thinking.

Users do not care what you upgraded, replaced, or migrated. They care if something breaks, slows down, or feels different without reason.

That is the standard.

Strong Product Managers treat transitions as first-class work; not background tasks. They plan them, de-risk them, align people around them, and execute with precision. Because every unnoticed transition builds trust. And every visible failure breaks it.

In a world of constant change, stability becomes your real product.

The T-Shaped Technical Product Manager

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It has been a long journey in the IT industry—moving from development into leadership roles. One thing remained constant: never standing still. Continuous learning, experimenting, and staying aligned with evolving technology shaped the way I approach products and teams today.

This journey led me to be recognized as a Technical Product Manager, sometimes referred to as a T-Shaped Product Manager. That said, this title does not imply knowing everything. It reflects a balance—depth in one area, with awareness across many.

What T-Shaped Really Means

A T-shaped profile combines broad understanding across disciplines (the horizontal bar) with deep expertise in one area (the vertical bar).

For a Technical Product Manager:

  • The depth lies in technology
  • The breadth spans business, user experience, delivery, and stakeholder alignment

This balance enables better decision-making, clearer communication, and more realistic product outcomes.

The Reality of Going Beyond Roles

Throughout my career, I have often gone beyond what was expected. Not to take over someone else’s role, but to ensure the product succeeds.

At the same time, I have been careful not to step into ownership that belongs to others.

This is where things get complicated.

Even when roles are clearly defined, boundaries are not always obvious in practice. Questions naturally arise:

  • Where does a Technical Product Manager stop and a Solution Architect begin?
  • How does a Product Manager differ from a Marketing or Growth Manager?

These overlaps are not just theoretical—they create real tension within teams.

When Ambiguity Turns Into Conflict

Role ambiguity often leads to friction in cross-functional teams.

Not because people are wrong—but because:

  • It challenges ownership
  • It disrupts comfort zones
  • It creates a sense of being questioned

In some cases, this tension becomes visible through reactions like:

“Do you want to join the development team?”

Statements like this are rarely about the actual discussion. They reflect discomfort when boundaries feel unclear.

If not handled carefully, such situations can lead to unhealthy team dynamics—where instead of focusing on building great products, individuals begin protecting their space.

And a team with internal conflict will rarely deliver its best work.

Defining the Roles (From Experience)

Product Manager

  • Owns the vision, problem space, and outcomes
  • Focuses on users, business goals, and prioritization

Technical Product Manager

  • Bridges business and technology
  • Understands systems, constraints, and trade-offs
  • Challenges decisions constructively while staying outcome-focused

Development Lead / Solution Architect

  • Owns the technical design and implementation approach
  • Ensures scalability, performance, and maintainability

How I Approach the T-Shaped Role

Being a T-shaped Technical Product Manager is not about control—it is about clarity and alignment.

From my experience, a few principles help maintain that balance:

1. Go Deep, But Not Too Far

Understanding technical details is important. Owning them is not.

The goal is to:

  • Ask better questions
  • Understand trade-offs
  • Avoid unrealistic expectations

Not to replace engineering decisions.

2. Stay Outcome-Focused

Discussions should always connect back to:

  • User impact
  • Business value
  • Long-term product direction

This keeps conversations grounded and reduces personal friction.

3. Respect Ownership

Every role exists for a reason.

Crossing boundaries occasionally is natural. Staying there is where problems begin.

4. Handle Challenges Carefully

Challenging ideas is necessary. Challenging people is not.

The difference lies in:

  • How questions are framed
  • The intent behind them
  • The respect shown in conversations

Where to Draw the Line

From experience, the line becomes clearer with intent.

Step in when:

  • Product outcomes are at risk
  • Trade-offs are unclear
  • Technical decisions impact user experience

Step back when:

  • The discussion is purely implementation-focused
  • The team is aligned on direction
  • Input starts becoming prescriptive

Final Thought

The T-shaped Technical Product Manager operates in a space that naturally overlaps with others. That overlap is not a problem—it is a necessity in modern product teams.

The real challenge is managing it with awareness.

It is not about knowing everything.
It is not about controlling decisions.

It is about connecting perspectives without creating conflict.

And when done right, it turns a group of individuals into a team that builds with clarity, not competition.

Why We Stopped Using PayPal: Lessons from an E-Commerce Experience

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As a business owner navigating the complexities of digital payments, my experience with PayPal left me with valuable lessons and, admittedly, a few frustrations. While PayPal is a market leader in payment gateways with a significant user base, our journey highlighted critical challenges when dealing with chargebacks and fraud prevention. This post isn’t about placing blame, but rather sharing our experience to help others facing similar issues.

The Scenario: Launching a B2C Platform for Digital Goods

We launched a B2C platform for digital goods, where customers could purchase and instantly receive their products via email. Due to the nature of digital goods—instantaneous delivery without a return or refund option—we implemented rigorous security measures to minimize risks. These included:

  • Strict transaction rules: Monitoring the number of transactions, purchase limits, and suspicious patterns like repeated CVV attempts.
  • Email verification: Blocking temporary emails and requiring 2FA (Two-Factor Authentication) for account access.
  • 3D Secure compliance: For card payments, we adhered to industry standards to ensure secure transactions.

Our cautious approach did cost us some potential sales, but it helped us safeguard against fraudulent transactions and reduce chargeback risks.

Fraudulent Behavior Patterns

E-commerce payment gateways often expose businesses to patterns of fraudulent behavior, including:

  • Mass Attempts: Hundreds of purchase attempts originating from the same IP address within a short timeframe, typically an indicator of automated or malicious activity.
  • Incremental Fraud: Fraudsters systematically testing multiple card numbers, expiration dates, or CVVs in an attempt to find a working combination and exploit the system.
  • Chargeback Abuse: Customers intentionally filing disputes or claiming “unauthorized transactions” after receiving goods or services, exploiting lenient refund policies.
  • Account Takeovers: Fraudsters gaining unauthorized access to legitimate user accounts to make purchases, often bypassing basic security checks.

Such activities not only strain security measures but also highlight the critical need for robust fraud prevention protocols to protect both businesses and customers.

The Challenge: Using PayPal for Payments

Given PayPal’s market presence, we integrated it as one of our payment gateways. The customer journey was simple: users would select PayPal at checkout, redirect to the PayPal platform to log in and authorize the payment, and return to our system with the transaction details. On paper, it looked like a seamless and secure process.

However, chargebacks labeled as “Unauthorized Transactions” began to surface, and they were a game-changer.

The Problem with Chargebacks

Chargebacks are an unavoidable part of e-commerce, but they often pose significant challenges, particularly when it comes to handling “Unauthorized Transactions.” Our experience highlighted several recurring issues:

  • Email Discrepancies: Some customers registered on our platform with one email and used a different email for their payment gateway account (e.g., PayPal). While this is technically valid, it created confusion and complications when chargebacks were filed, making it difficult to verify user identities.
  • User Authorization Uncertainty: Even after implementing robust security measures like 2FA (Two-Factor Authentication) for both our platform and payment gateway-associated emails, customers continued to flag transactions as “Unauthorized.” This raised questions about who truly had access to and control over these accounts, leaving businesses in a vulnerable position during disputes.
  • Family or Shared Accounts: Payment accounts shared among family members or used for group purchases often led to disputes when one party claimed not to have authorized the transaction, even though the purchase was made using legitimate account credentials.
  • Delayed Chargebacks: Customers sometimes initiated chargebacks weeks or months after the purchase, long after the digital goods had been delivered. This created a scenario where businesses had limited ability to dispute the claims, especially for non-returnable digital products.
  • Lack of Evidence Weighting: Evidence submitted to dispute a chargeback—such as delivery confirmations or user authentication logs—seemed to carry less weight in decisions, leaving businesses with little recourse.

These issues underscore the complexity of managing chargebacks and the importance of both customer education and proactive fraud prevention measures to reduce disputes and protect the business.

Our Solution: Removing PayPal

After losing a significant amount to chargebacks and exhausting every possible option to improve transaction security, we made the difficult decision to remove PayPal as a payment gateway. This was not a decision we took lightly, as we fully recognize the value and widespread adoption of PayPal in the e-commerce world. It is one of the most trusted and convenient payment platforms for customers, offering seamless transactions and a familiar user experience.

However, for a digital goods platform like ours—where fraud prevention is critical and chargebacks pose unique challenges—we found it increasingly difficult to balance security and usability with PayPal. Our business model requires us to ensure the legitimacy of every transaction because digital goods, once delivered, cannot be returned or refunded. Despite our best efforts, including robust fraud prevention measures, the chargeback process with PayPal created vulnerabilities that we couldn’t effectively mitigate.

Why We Couldn’t Make PayPal Work

  1. Limited Verification Options: Unlike card payment gateways that utilize mechanisms like 3D Secure, PayPal’s system offered limited verification capabilities for customers purchasing digital goods. This made it harder to authenticate the legitimacy of transactions.
  2. Chargeback Risks: For digital goods, chargebacks labeled as “Unauthorized Transactions” often left us with little recourse, as digital products cannot be physically returned. Despite providing evidence of delivery and authentication, disputes often ended in favor of the customer.
  3. Fraudulent Behavior: PayPal’s user-friendly interface, while beneficial for customers, made it easier for fraudsters to exploit the platform. Patterns of incremental fraud, shared accounts, and delayed chargebacks created significant financial risks.
  4. Mismatch with Our Security Standards: Our platform relied on strict security protocols, such as 2FA, email validation, and IP monitoring. Integrating PayPal, with its less stringent user verification, created inconsistencies that exposed us to unnecessary vulnerabilities.

Lessons Learned

While PayPal remains an excellent choice for many businesses, particularly those dealing with physical goods or services that allow returns, it proved to be a poor fit for our specific needs. For digital goods platforms, where fraud prevention and irreversible transactions are critical, these challenges made PayPal an unsustainable solution.

This decision has allowed us to focus on alternative payment gateways that better align with our security requirements, offering advanced fraud detection, tighter user verification, and more robust chargeback dispute mechanisms.

A Word of Advice to Other Businesses

If your business model involves digital goods or services, consider the following before integrating PayPal or similar platforms:

  • Assess Your Fraud Risks: Evaluate the risk of chargebacks and unauthorized transactions in your industry.
  • Explore Additional Verification Layers: Look for payment gateways offering tools like 3D Secure, enhanced fraud detection, and multi-factor authentication.
  • Monitor Patterns: Continuously analyze customer behavior to identify potential fraud trends.
  • Communicate Clear Policies: Set clear refund and chargeback policies to minimize misunderstandings and disputes.

Removing PayPal was a tough but necessary decision for our business. While we appreciate its role as a leading payment gateway, we had to prioritize the security and sustainability of our platform. This experience has taught us valuable lessons that we hope will help others navigate similar challenges in the ever-evolving e-commerce landscape.

Still Seeking Solutions

While we’ve moved away from PayPal, the challenges we faced have not discouraged us from seeking better solutions to balance security, user convenience, and fraud prevention in our payment processes. Removing PayPal was a strategic decision based on our specific needs as a digital goods platform, but the broader issue of managing fraud and chargebacks remains a significant focus.

Advocating for Better Chargeback Mechanisms

As we navigate these challenges, it’s evident that the industry as a whole needs better mechanisms to address chargebacks, particularly for digital goods. We believe:

  • Payment gateways should provide more context-specific options for merchants dealing with non-returnable items.
  • Evidence provided by merchants, such as delivery confirmations or customer authentication logs, should carry greater weight in chargeback disputes.
  • Collaboration between merchants, payment providers, and customers needs to improve to prevent misuse of chargeback systems.

A Commitment to Continuous Improvement

Despite the hurdles, we remain committed to finding solutions that protect our platform and customers. The e-commerce landscape is constantly evolving, and staying ahead requires a mix of innovation, collaboration, and adaptation. We are optimistic that with continued effort, we’ll achieve a secure and efficient payment ecosystem that aligns with our business needs and customer expectations.

For now, we continue to test and implement measures that not only reduce fraud but also enhance the trust and transparency of our platform. This is an ongoing journey, and we’re determined to turn these challenges into opportunities for growth and improvement.

Disclaimer: This post reflects my personal experience and is intended to share insights with other professionals. It does not represent PayPal’s official practices or policies.

The Tech Alchemy of Product Management

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In today’s fast-paced world of business and technology, it’s easy to fall into the trap of believing that certifications alone define your capabilities as a project or product manager. Over the years, I’ve completed certifications like the Google Project Management via Coursera and earned my CSPO (Certified Scrum Product Owner) via Scrum Alliance. I’ve also taken few micro-certifications. While these courses taught me valuable knowledge about tools, frameworks, and methodologies, the truth is, project and product management goes far beyond certifications.

These programs helped me understand the core elements and gave me exposure to important practices in the industry. However, I truly mastered these skills only by getting my hands dirty, leading teams, and solving real-world challenges. I’ve realized that project and product management can’t be entirely taught in a classroom—it’s about leadership, handling tough situations, and making decisions when everything’s on the line.

Leadership Over Certifications

Being a project or product manager is more about leadership than technical expertise. Leadership is a skill that isn’t granted by a certificate; it’s developed through experience. Some people excel in technical skills but struggle with leadership, while others naturally have the ability to inspire, organize, and lead without formal training.

Simon Sinek, a leadership expert, illustrates this well with his example from the Marine Corps. He explains that potential officers undergo six weeks of intense training where they can quit at any time. This training is designed to weed out those who don’t want to be leaders. As Sinek puts it, “The first criterion to being a leader is you have to want to be one.” Leadership is tough—it can be thankless, lonely, and incredibly challenging. But in project and product management, it’s what makes the difference between success and failure.

One thing I’ve learned from my experiences is that no certification can prepare you for the real-world challenges you face in the field. For instance, I once led a project demonstration where everything seemed perfect—until the solution failed due to an unexpected angle of sunlight affecting the camera. This was something we hadn’t encountered before, and no textbook or course could have prepared me for the heat of that moment, both literally and figuratively. I had to accept the failure gracefully and quickly think on my feet, acknowledging the problem while managing the client’s expectations, all while battling my own internal guilt.

Balancing Personal and Professional Commitments

Being a project manager often requires balancing personal and professional responsibilities—another aspect no certification can fully prepare you for. I remember a time when my employer used me as an example of dedication to others because I traveled across the country for a work commitment the day after my wedding. This might seem extreme to many, but I had made a commitment well before my marriage date was set. It was my responsibility to manage both my personal and professional commitments, and I did so by discussing it with my family and gaining their support rather than walking away from the commitment.

Leadership in project and product management often means making these tough calls—balancing your time, keeping your promises, and staying accountable, no matter how challenging the circumstances.

Practical Experience vs. Theoretical Knowledge

It’s easy to say things like, “know your customer” or “interview your users,” but putting these principles into practice is much more difficult. During one project, I found myself standing next to an attendance device at a hospital, observing how random person interact with the device and how staff used it to clock in and out. On the surface, this might sound simple, but the discomfort of standing there as a stranger, taking mental notes on behavior, is not something a certification teaches you. It’s the hands-on learning and the real-time observations that help you understand your customer in ways a classroom cannot. A funny aspect, a guest used this device to many times on different days to comb hair.

Another time, I launched a solution for a client whose business handled thousands of dollars in weekly transactions. The pressure of ensuring nothing went wrong was immense. I couldn’t sleep or eat, not because it was part of my job description, but because I knew the stakes were incredibly high. I stayed awake, monitoring every detail, even though I wasn’t being paid for those extra hours. Certifications can teach you how to plan for a launch, but only experience can prepare you for the reality of it.

Leadership in High-Stakes Situations

Leadership is about how you handle pressure, especially when things go wrong. Simon Sinek often speaks about leadership as the responsibility to help those around you rise, even when it’s hard. Leadership isn’t about delegating tasks or following a checklist—it’s about stepping up when the stakes are high and taking responsibility for the outcome.

No certification prepared me for the time when I was in front of a room of clients, sweating both from the physical heat and the internal pressure, when a solution failed due to a reason no one could have foreseen. Leadership, not certification, is what allowed me to remain calm, accept the failure, and offer a plan for improvement.

Handling Unique Challenges

Every project brings its own set of unique challenges, and learning by doing is the only way to normalize those experiences. Certifications are useful for providing a foundation, but it’s the real-world situations that truly shape you as a manager. Whether it’s troubleshooting technical failures on the fly, balancing personal and professional commitments, or standing by a solution you launched while facing the risks, the true essence of project and product management lies in how you navigate uncertainty and lead in moments of crisis.

Conclusion: Experience Over Certification

In the end, while certifications like the Google Project Management Course or CSPO have given me valuable tools, the reality is that project and product management is about leadership, not certificates. It’s about having the ability to make tough decisions, take responsibility, and guide a team through unexpected challenges. Certifications provide a strong foundation, but leadership is something you develop through practice, persistence, and navigating real-world challenges. Leadership is a skill anyone can learn, but it’s only mastered through experience. As a project or product manager, your real growth happens when you’re in the field, handling situations no certification could have ever predicted.

Technical Product Managers: The Bridge Between Development and Business Success

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In today’s fast-paced technology landscape, Technical Product Managers (TPMs) are essential for the success of modern product launches and continuous improvements. TPMs uniquely blend technical expertise with strategic business acumen, allowing them to bridge the gap between development teams and business stakeholders. Unlike traditional product managers, TPMs dive deeper into the technical side, working closely with engineers while keeping an eye on the product’s market fit and customer satisfaction.

As someone with experience in full-stack web development and AI/machine learning engineering, I’ve seen firsthand how crucial the TPM role is in delivering successful, scalable products. In startups especially, where resources are limited, the ability to wear multiple hats—including solution architect, project manager, and developer—becomes critical. This comprehensive skill set makes Technical Product Managers a driving force behind well-executed product launches and ongoing product success.

The Role of a Technical Product Manager in Product Development

In any successful product launch, the Product Manager is responsible for ensuring that the right product is built—one that aligns with customer needs, market demands, and business goals. Their role is to define the vision, prioritize features, and make sure the product addresses the right problems. However, the Technical Lead and the Development Team are responsible for building it right. This means they focus on the technical execution, ensuring the product is developed with scalability, performance, and maintainability in mind.

The Technical Product Manager bridges these two areas, ensuring that the product being built not only meets the business objectives but is also technically sound, guiding both the Product Manager and the technical team to stay aligned on both the “what” and the “how” of product development.

Product Manager (PM)

PMs focus on defining the product vision, understanding customer needs, and aligning the roadmap with business objectives. Their primary goal is to ensure the product meets the market’s demands.

Delivery Manager

Delivery Managers oversee the execution of the product, ensuring timelines, resources, and budgets are on track. They work closely with the engineering team to deliver on the defined goals.

Technical Product Manager (TPM)

A TPM does more than manage the product; they dive deep into the technical side, understanding the architecture, technology stack, and development hurdles. They ensure the product is feasible, scalable, and aligned with both business goals and technical realities.

Where Technical Product Managers Thrive

TPMs are particularly valuable in certain environments and projects where their skill set stands out:

Highly Technical Products

Products involving APIs, machine learning, cloud services, or complex backend architectures benefit immensely from TPMs. They can translate technical constraints to business leaders while guiding developers in building the right solution.

Startups

In startups, where teams are lean, TPMs play multiple roles. I’ve often taken on responsibilities like designing solution architectures, engaging developers, and ensuring the product’s technical alignment with business needs. Startups need this versatility to stay competitive and efficient.

Cross-functional Teams

When multiple teams—like frontend developers, backend engineers, and machine learning specialists—work together, a TPM bridges the gaps, ensuring smooth communication and integration across departments.

My Experience Bridging Technical Teams

There have been many adventures but I would like to share one piece from my past where we built a facial recognition-based attendance solution, involving both a web team skilled in APIs and a machine learning team focused on training AI models. The teams had little overlap in expertise, which led to challenges in integrating their work into a cohesive product.

With my technical knowledge and leadership skills, I acted as the bridge between these teams. I worked with the web team to design an API that could seamlessly handle data flow from the front end, while coordinating with the machine learning team to ensure their models were integrated efficiently. This collaboration resulted in a scalable, real-time solution that effectively processed facial recognition data for attendance tracking. My technical understanding allowed me to foresee bottlenecks and prevent them before they became major issues.

The Role of a Technical Product Manager in Product Success

A successful product launch requires coordination, technical insight, and stakeholder management—all key strengths of a Technical Product Manager (TPM). TPMs play a critical role in bridging the gap between development teams and business leaders, managing complex technical details, and ensuring that everyone is aligned toward the same goal.

  • Wearing Multiple Hats:
    During product launches, TPMs often juggle multiple responsibilities, including solution architecture, project management, and technical leadership. For example, while launching a scalable AI-powered platform, I had to design the backend infrastructure, manage timelines, and oversee the development team—all while ensuring that the technical decisions were aligned with the launch’s business objectives and budget constraints.
  • Solution Design:
    In the high-pressure phase of product launch, TPMs take a lead role in designing systems that are both scalable and reliable. I’ve had to design backend architectures that could handle a sudden influx of users post-launch, ensuring that the infrastructure was robust enough to maintain performance under growing traffic without disruptions.
  • Developer Engagement:
    TPMs play a key role in keeping developers aligned with the product’s vision and technical requirements. I’ve worked closely with development teams to ensure they understand both the technical challenges and the broader business context. This prevents common issues like technical debt and keeps the project on track, ensuring a successful launch.
  • Stakeholder Management:
    One of the most critical roles of a TPM during a product launch is managing expectations and communication with stakeholders. Whether it’s business leaders, marketing teams, or external clients, keeping everyone informed and aligned is essential. I’ve managed stakeholders by providing regular updates, explaining technical decisions in business terms, and ensuring that launch goals remain clear to all parties. This not only ensures smoother decision-making but also reduces last-minute changes that can jeopardize a launch.

Key Skills and Qualities of a Technical Product Manager

Technical Product Managers bring a unique blend of skills that make them critical for product success. From my experience, here are the key qualities that make TPMs stand out:

  1. Technical Expertise: A TPM needs in-depth knowledge of the technology stack, including APIs, cloud infrastructure, and AI/ML workflows. This allows them to validate technical solutions and troubleshoot issues alongside developers.
  2. Strategic Vision: TPMs must always consider how technical decisions align with business goals. They need to ensure that the product is not only functional but also profitable and scalable.
  3. Problem-solving and Bottleneck Prevention: One of my primary responsibilities is identifying and eliminating bottlenecks early. Whether it’s optimizing a machine learning pipeline or ensuring that APIs are scalable, TPMs must proactively address challenges before they hinder progress.
  4. Collaboration and Communication: A TPM serves as the bridge between technical teams and non-technical stakeholders. My role as a liaison between web and machine learning teams on various projects has taught me that clear communication and collaboration are key to success.
  5. Empathy and Leadership: A TPM must balance user needs with developer constraints. I make sure to approach problems from both perspectives, ensuring that the final product meets customer expectations while supporting developers with clear direction and technical insights.
  6. Agility and Adaptability: In fast-paced environments, TPMs must be able to pivot quickly, adjusting to new challenges or changes in market demand. My experience in startups has honed my ability to remain agile, ensuring that projects stay on course even when priorities shift.

Conclusion: Building the Right Solution the Right Way

The role of a Technical Product Manager is critical to ensuring product success, especially in highly technical fields and startup environments. TPMs not only focus on building the right solution for customers but also ensure that it’s being built the right way. My experiences in AI, full-stack web development, and startups have shown that TPMs are indispensable in managing technical complexity, aligning development teams, and driving successful product launches.

By bridging the gap between technical teams and business stakeholders, TPMs provide the leadership needed to ensure a product’s success, both at launch and through continuous improvement. With the right skills and mindset, a Technical Product Manager can be the key to delivering products that scale, innovate, and meet the market’s demands.

Building a Product from Scratch: A Step-by-Step Guide for Startups

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Building a product from scratch is an exciting journey—one that offers the opportunity to create something innovative, solve real-world problems, and, hopefully, make a lasting impact in the market. However, the process of building a product from the ground up also comes with its own set of challenges, risks, and pitfalls. For startups, getting it right from the start can make all the difference between success and failure.

As someone who has navigated this terrain and learned through trial and error, I understand both the excitement and the pressure of starting fresh. In this guide, I’ll share personal experiences and insights gained over the years, as well as a step-by-step approach to building a successful product from scratch.

Challenges of Joining Existing Projects vs. Building from Scratch

When you’re part of a startup, building from scratch is a whole different game compared to working on existing products. I’ve had experiences working in both environments—joining established projects where decisions were already made and starting from a blank canvas. Each has its pros and cons.

In established projects, there’s often a structured foundation, and it’s easier to blend into an existing workflow. However, sometimes you inherit baggage—legacy systems, clunky code, or team dynamics that may be resistant to change. I recall one project where, as a frontend developer, I was told we wouldn’t use Bootstrap because the senior team believed it was bloated with unnecessary features. Instead, we aimed to achieve responsiveness and cross-browser compatibility with minimal custom CSS. Fast forward one year: the CSS file became larger than the entire Bootstrap library! It was clear we could have saved time and effort by leveraging existing frameworks.

On the other hand, building a product from scratch offers flexibility and the freedom to define the project’s DNA. You get to make decisions that shape the future of the product. But it also requires foresight, careful planning, and an openness to learning from mistakes. It’s easy to get sidetracked by “ShaShka” features (as we called them)—fancy, non-essential bells and whistles that can derail focus from core functionality. I experienced this firsthand while leading a team tasked with building a proof of concept under a tight deadline. We got bogged down with non-core features and ended up sacrificing essential components. Ultimately, the project didn’t win the contract, and the team was disillusioned.

Building a product is a marathon, not a sprint. It’s crucial to adopt the right mindset and prepare for an ongoing, iterative process.

A Step-by-Step Guide to Building a Product from Scratch

To guide startups on this journey, let’s break down the process into actionable steps that can help you avoid common mistakes, deliver on time, and build a product that stands out.

1. Start with a Strong Vision

Everything begins with a clear vision. What problem are you solving? Who is your target audience? Why is your product important? Your vision should be simple but compelling, providing a North Star for your team and stakeholders to follow.

The vision isn’t just a “nice to have”; it’s essential for guiding every decision that comes later. It keeps you focused on the core objectives and ensures that you don’t get distracted by features or trends that don’t align with your ultimate goals. Make sure that everyone involved—whether it’s developers, designers, or business leaders—understands and buys into this vision. Here are some abstract-level tools to help:

  • Product Vision Board: A visual tool to communicate long-term goals and strategy.
  • North Star Metric: A single key metric that represents your product’s core value to users.
  • Personas: Fictional profiles representing target users, ensuring the product addresses their specific needs.
  • Lean Canvas: A one-page framework that outlines key elements like customer segments, problems, and solutions.
  • KPIs: Metrics to track progress and ensure alignment with business goals.

2. Validate Your Idea

Before you commit resources to development, validate your product idea. This is a critical step that many startups skip in their eagerness to start building. Validation means testing your idea with real users, potential customers, or experts in the industry.

You can start small: create surveys, conduct interviews, or build a basic prototype (MVP) to gather feedback. Early validation helps you identify whether your product solves a real problem and whether there’s a market for it. This process can save you time and money by identifying issues before you’re too deep into development.

Here are some effective methods to validate your product idea:

  • Minimal Viable Product (MVP): An MVP is the simplest version of your product that includes only the core features. It allows you to test the waters with real users and gather feedback before committing to a full build. By launching an MVP, you can see how your target audience reacts and make data-driven decisions on how to proceed.
  • Surveys and Interviews: Conducting surveys and interviews with potential customers is a quick way to validate demand. Ask targeted questions to understand user pain points, preferences, and whether your product addresses their needs. This approach gives you direct insights into what your audience wants.
  • Mockups and Prototypes: Creating visual mockups or interactive prototypes can help bring your idea to life without extensive development. Tools like Figma or Adobe XD allow you to showcase a clickable version of your product, giving users something tangible to react to. Feedback from mockups can guide design and functionality decisions early in the process.
  • Landing Pages: A simple landing page describing your product, paired with a call to action (e.g., email signups or pre-orders), can gauge interest. It’s a quick way to validate whether people are excited about your product before you invest in development.

Please note, as a goodwill gesture, many people will say your idea is good. But as a startup, it’s your job to assess whether these people are willing to make payments. After all, what’s the use of a great idea that nobody wants to buy?

Using these validation methods helps avoid building a product nobody wants. It ensures your time and resources are invested wisely, focusing on solutions that resonate with real user needs.

3. Build a Minimal Viable Product (MVP)

When building from scratch, it’s tempting to create the perfect product right away. However, that’s a recipe for over-commitment and delays. Instead, start with a Minimal Viable Product (MVP)—a version of the product that includes only the core features necessary to address the primary pain point.

The idea behind an MVP is to get something functional into users’ hands quickly. By doing this, you can start gathering real-world feedback that will shape the product’s future iterations. In my experience, working on an MVP also helps the team stay focused on essential features, preventing scope creep (like those unnecessary “ShaShka” features).

4. Prioritize Features

Once you’ve validated your product idea, the next crucial step is to determine which features to develop first. Not all features are created equal—some will have a much larger impact on your product’s success, while others may be nice-to-haves that can wait for later iterations. Effective feature prioritization helps keep your team focused, ensures efficient use of resources, and aligns your product with business goals. Here are some popular methods for prioritizing features:

Here are some common methods to help:

  • MoSCoW Method: Categorizes features into Must Have, Should Have, Could Have, and Won’t Have to simplify decision-making. I have shared some more insights here
  • Now, Next, Later: Organizes features based on timing—what to work on now, next, and later—ideal for agile teams.
  • RICE Framework: Prioritizes features based on Reach, Impact, Confidence, and Effort using the formula:
    RICE Score=(Reach×Impact×Confidence)/Effort
    ​This helps determine the highest-value features by balancing potential impact against the effort required.
  • Weighted Scoring: Assigns weight to different factors (e.g., customer engagement, revenue potential, technical complexity) and scores features based on these factors. The total weighted score determines the priority, allowing for a more objective, data-driven approach to feature prioritization.

These frameworks help ensure that teams focus on high-value features aligned with both customer needs and business goals.

5. Assemble a Strong, Balanced Team

A product is only as strong as the team behind it. When building a product from scratch, the team composition can make or break the project. You need a balance of technical and creative minds, alongside people who understand the business and market.

In my early career, I was often just part of the development team, while senior members made the core decisions. Now, as a product manager, I’ve learned that strong leadership isn’t just about telling people what to do—it’s about assembling the right people, empowering them, and creating a culture of open communication. Choose people who are flexible, passionate, and willing to wear multiple hats in the early stages.

Every team benefits from having alpha players—those high-performing individuals who bring a strong combination of skill, drive, and leadership. However, a product can’t thrive on alpha players alone; you need a well-rounded team with diverse strengths. To ensure balance, the Skill-Will Matrix is a valuable tool for assessing team members based on two dimensions:

  • Skill: Their ability to perform tasks effectively.
  • Will: Their motivation and drive to excel.

The Skill-Will Matrix divides team members into four quadrants:

  1. High Skill, High Will: These are your natural leaders and alpha players, capable of delivering high-quality work with minimal guidance.
  2. High Skill, Low Will: Skilled team members who may lack motivation. You’ll need to re-engage them through new challenges or meaningful projects.
  3. Low Skill, High Will: Motivated individuals eager to learn. With the right guidance and training, they can grow into valuable contributors.
  4. Low Skill, Low Will: These members may need extra attention to assess whether they can contribute effectively or if other roles suit them better.

6. Stay Agile and Iterate

Building a product from scratch requires flexibility and the ability to adapt to changing circumstances, customer feedback, and new insights. Adopting an Agile mindset from the start ensures that your team can iterate quickly, make adjustments based on real-time data, and stay aligned with business goals. The core principle of Agile is continuous improvement, delivering value in small increments, and being responsive to feedback.

Regardless of the Agile framework you choose—whether it’s Kanban, Scrum, or another—incorporating key ceremonies can significantly streamline development and keep your team aligned:

  • Daily Standup: A brief, daily check-in where team members share progress, challenges, and next steps to ensure transparency and alignment.
  • Retrospective: A regular reflection on what went well and areas for improvement, promoting continuous growth and process refinement.
  • Align with Roadmap: Frequent reviews to ensure current tasks align with the overall product vision and long-term objectives.
  • Limit Work in Progress (WIP): Restrict the number of tasks in progress to enhance focus and reduce inefficiency.
  • Backlog Grooming: Regularly prioritize and refine the backlog to ensure the team is always working on the most valuable tasks.
  • Sprint Planning: Set clear, achievable goals for each sprint, keeping the team focused on delivering impactful features.

7. Engage Stakeholders Early and Often

Communication with stakeholders—whether they’re investors, customers, or internal team members—is key to the success of any product. Startups sometimes make the mistake of involving stakeholders too late in the process, which can result in misaligned expectations.

When we built a proof of concept under a tight deadline, we lost focus by trying to please too many stakeholders at once. This taught me the importance of clear, continuous communication and expectation management. Engage stakeholders early, and make sure they’re part of the decision-making process throughout.

A stakeholder communication plan ensures that the right people receive the right updates at the right time. This plan includes identifying stakeholders, determining communication frequency, and choosing appropriate methods like emails, meetings, or reports.

Interest vs. Influence Matrix

The Interest vs. Influence Matrix categorizes stakeholders based on how much they care about and impact the project:

  • High Interest, High Influence: These are your primary stakeholders, such as key decision-makers and executives. They require frequent, detailed communication through meetings, progress reports, and real-time updates. Keep them closely involved in major decisions.
  • High Interest, Low Influence: These stakeholders care about the project but may not have decision-making power. Use regular updates via email or presentations to keep them informed, ensuring they feel included in the process.
  • Low Interest, High Influence: Stakeholders with influence but low day-to-day involvement (e.g., senior leaders). Provide periodic, high-level updates to keep them in the loop without overwhelming them with details.
  • Low Interest, Low Influence: These stakeholders don’t require frequent updates. Minimal communication like status emails or quarterly reports may suffice, ensuring they’re aware of the project but not deeply involved.

Tailor your communication mode—meetings, emails, or dashboards—to fit each group’s needs, ensuring everyone stays aligned throughout the project.

8. Prepare for Scaling

As your product grows, so will its demands. To handle increased traffic, users, and data, it’s essential to build your technical infrastructure with scalability in mind from the outset. Failing to plan for growth can lead to performance bottlenecks, higher costs, and operational headaches down the road. Here’s how to prepare for scaling effectively:

  • Scalable Architecture: Design a flexible, scalable architecture that can handle growth without requiring complete overhauls.
  • Database Selection: Choose a database that can scale horizontally (adding more servers) or vertically (upgrading server capacity) as data grows.
  • Development Frameworks: Select development frameworks with proven scalability and strong community support. Having a robust community behind the tools you use ensures you can access resources, updates, and troubleshooting support when scaling challenges arise.
  • Monitoring and Performance Tools: Integrate tools for monitoring system performance, load balancing, and error detection.

By building scalability into your product from the beginning, you can avoid technical bottlenecks, reduce costs, and ensure your product continues to perform smoothly as demand increases.

Conclusion: Focus on the Infinite Game

Building a product from scratch is a complex but rewarding journey, especially for startups. Success comes from more than just technical skills—it requires clear vision, effective validation, thoughtful feature prioritization, and assembling a strong, balanced team. Staying agile and engaging stakeholders early ensures your product evolves in alignment with both market needs and business goals.

Scalability is another critical factor to consider from the beginning, as your product will grow, and so will its demands. By planning for this growth—whether through scalable architecture, robust tools, or efficient frameworks—you’ll prevent bottlenecks and ensure smooth operations down the road.

Ultimately, the key to success is staying adaptable, learning from mistakes, and focusing on delivering real value. With the right mindset, tools, and team, your product will be well-positioned to thrive and make a lasting impact in the market.